We consider random effects meta‐analysis where the outcome variable is the occurrence of
some event of interest. The data structures handled are where one has one or more groups …

Background In meta-analyses of a binary outcome, double zero events in some studies
cause a critical methodology problem. The generalized linear mixed model (GLMM) has …

Objectives: To compare the performance of different meta‐analysis methods for pooling
odds ratios when applied to sparse event data with emphasis on the use of continuity …

Background Systematic reviews and meta-analyses of binary outcomes are widespread in
all areas of application. The odds ratio, in particular, is by far the most popular effect …

We examine two strategies for meta‐analysis of a series of 2× 2 tables with the odds ratio
modelled as a linear combination of study level covariates and random effects representing …

Earlier work showed how to perform fixed‐effects meta‐analysis of studies or trials when
each provides results on more than one outcome per patient and these multiple outcomes …

A problem which occurs in the practice of meta-analysis is that one or more component
studies may have sparse data, such as zero events in the treatment and control groups. Two …

Meta-analysis has been widely used to synthesize evidence from multiple studies for
common hypotheses or parameters of interest. However, it has not yet been fully developed …

The Mantel‐Haenszel (MH) method has been used for decades to synthesize data obtained
from studies that compare two interventions with respect to a binary outcome. It has been …

Background Standard random-effects meta-analysis methods perform poorly when applied
to few studies only. Such settings however are commonly encountered in practice. It is …